Knowledge Infrastructures and Intranets : Reengineering for learning

Feature

posted 1 Aug 1997 in Volume 1 Issue 1

Knowledge Infrastructures and Intranets : Re-engineering for learning

In the first of a two part article, Eelco Kruizinga, Gertjan van Heijst and Rob van der Spek of Kenniscentrum CIBIT, in the Netherlands, discuss knowledge infrastructures, the support systems of organisational structures and the guidelines necessary to develop a knowledge based organisation.

1. Introduction

Starting from our views on knowledge management, this article will introduce the concept of knowledge infrastructures. A knowledge infrastructure is defined as:

A support system, consisting of the set of organisational structures and guidelines, and (both technical as well as non-technical) means that an organisation deploys to support learning processes in order to meet the knowledge management objectives of the organisation in an efficient manner.

In this definition, a knowledge infrastructure is the means for and result of knowledge management. Through examples of components of a knowledge infrastructure, we hope to clarify that knowledge management is about the generation of synergy between the components. Through this synergy, knowledge infrastructures can provide the backbone for learning processes in organisations.

The implementation of components of a knowledge infrastructure will be discussed in relation to the possibilities of intranets as places for learning in the knowledge infrastructure. We will argue that intranet technology provides opportunities for re-engineering existing knowledge infrastructures for better, synergetic learning.

In this article, knowledge infrastructures will be viewed from two perspectives: a collective perspective and an individual perspective.

The collective perspective on knowledge infrastructures shows us the coherence between the components, whereas the individual perspective shows us what the infrastructure looks like when it meets with the individual knowledge worker. Using the concept of knowledge cockpits, we will define the relation between the individual knowledge worker and the collective knowledge infrastructure.

2. Knowledge management: the foundation of continuity and innovation

What is knowledge management all about? Throughout the ages, people had to cope with change: for example, in 1513 Machiavelli wrote of the 'tremendous changes which we see taking place around us day after day, of which no one had the slightest foreboding.' The world around him was changing rapidly. Since then, the rapidity with which changes pursue one another has continually increased. But organisations are still required to respond satisfactorily to political, social, economic and technological developments.

Knowledge and, in a broader context, competence (attitude, skills and knowledge) comprise the heart of a business. Meeting current and future challenges requires optimum utilisation of the available knowledge, but it also demands continuous improvement of the knowledge in the organisation, based on internal and external learning experiences. An increasing number of companies are therefore making the management of knowledge a top priority, and for good reason. Any company looking for continuity is well served by knowledge management.

Knowledge management answers questions like: how do I ensure crucial knowledge remains within the organisation even though we employ a great deal of flexible manpower? How can we learn quicker than our competitors? How can we ensure that when our people in Amsterdam learn something, that knowledge is also made available in London or any other place in the world?

3. What does effective knowledge management mean in practice?

Effective knowledge management is related to the development of new knowledge, consolidation of knowledge already acquired, distribution of knowledge in the organisation, combining the knowledge available and ensuring that the best knowledge is being used (van der Spek et al., 1997). In practice it is possible to identify an organisation which is succeeding in knowledge management terms by the following characteristics:

All the knowledge available in the organisation is put to optimum use. The best knowledge is accessible at every place and time it is required.

The internal market of knowledge producers and users functions optimally.

Crucial knowledge is successfully converted into fixed capital in the form of processes, structures and patents.

Knowledge is used successfully in the development of innovative products and services to improve the process.

Individual learning experiences (both negative and positive) are turned into knowledge and made available to whom it may concern.

Any risks regarding critical knowledge are evaluated well in advance.

Business strategy and knowledge policy are well attuned. In this respect, the value disciplines of Treacy and Wiersema (1995) provide a useful framework for coupling business strategy to knowledge policy. In their value discipline framework, Treacy and Wiersema state that an organisation should focus on one particular value discipline as a strategic option. The three value disciplines that are discerned in the framework are customer intimacy (providing a customised solution to a selected set of customers), operational excellence (providing a best-cost solution) and product leadership (providing the most innovative solution). Naturally, focussing on a particular value discipline dictates the ways in which organisational learning should take place.

These characteristics show us that knowledge management addresses both knowledge policy issues (what knowledge do we need, now and in the future?) as well as the design and maintenance of a knowledge infrastructure supporting the knowledge policy. The introduction of knowledge management is a learning process in itself. We adopt an iterative approach in which knowledge policy formation and knowledge infrastructure design and maintenance influence each other. Each iteration leads to a learning process resulting in two-way adaptations of knowledge policy and support system.

Figure 1 - A knowledge infrastructure

4. Knowledge infrastructures as support systems

We have defined knowledge infrastructures as support systems for knowledge management. The definition indicates that a knowledge infrastructure has an organisational and a technical dimension. An organisation that buys a system with all kinds of features to support knowledge sharing, but fails to reward knowledge sharing, does not get the expected results. On the other hand, an organisation that stimulates knowledge sharing, but does not provide the necessary facilities, will be disappointed too.

Knowledge management goals and organisational culture are important determinants for the design of a knowledge infrastructure. Knowledge management goals, as laid down in knowledge policies, determine what knowledge is to be developed, consolidated and distributed throughout the knowledge infrastructure. These knowledge policies could be regarded as the learning plans of an organisation, much in the sense of the learning plans we know of traditional education. Organisational culture determines in what way the knowledge infrastructure should be implemented in an organisation.

Learning for innovation and learning for productivity

When people refer to learning processes in organisations, one often refers to the development of new knowledge. In this view, learning is seen as a tool for innovation. However, learning processes can also be aimed at application of the best existing knowledge. In this latter view, learning is seen as a tool for knowledge productivity. Depending on the ambition level one has with a knowledge policy, one can either focus on improving the productivity of existing knowledge (which is normally an ambition level for first-time knowledge management efforts), focus on facilitating innovation (thus seeing the development of new knowledge as target of knowledge management) or focus on an integral knowledge infrastructure, in which knowledge productivity as well as innovation processes are well attuned.

5. Learning processes and components of a knowledge infrastructure

It should be noted that no turnkey solutions are available for knowledge infrastructures. Due to strategic, cultural and technical contingencies, knowledge infrastructures are custom-made. However, it is possible to discern a number of components that, be it in different configurations, often form part of a knowledge infrastructure. We will discuss some of these components in more detail by coupling them to sample learning processes they support. This is done to emphasise that knowledge infrastructures are support systems for learning processes in organisations.

In Figure 2 below, the components of a knowledge infrastructure support learning processes in organisations. The components themselves ideally are interconnected, so that learning experiences are exchanged.

Figure 2

5.1. Learning from research: R&D department

In many organisations, R&D departments are the traditional source of new knowledge. In technically oriented organisations it is often the case that R&D hold a de facto monopoly on new knowledge. R&D departments normally are the interface to fundamental knowledge that is developed at universities. That this can be fruitful, as shown in the box below.

5.2. Learning from history: the archives

An important function of a knowledge infrastructure is to prevent knowledge erosion. Recording knowledge is done at the archives of an organisation. The records stored provide an organisational memory with tremendous possibilities for learning. Records may contain product and service related knowledge such as product specifications and design decisions, may contain knowledge about customers, but may as well contain knowledge about employees: this enables organisations to find the right person for a job or problem.

R&D departments and universities: knowledge interfacing

The Dutch newspaper NRC Handelsblad reported on May 31st 1997 that an American investigation carried out for the National Science Foundation, showed that industrial patents increasingly build on results of fundamental scientific research. Almost 75% of citations refer to research done at universities and government funded research institutions.

5.3. Learning from the shop floor: lessons learned

To collect lessons learned is a way to be able to capture important knowledge that can improve day-to-day work. The collection and processing of lessons learned resembles very closely the sampling of ideas in total quality management. Lessons learned, both positive and negative, are an important source within the knowledge infrastructure. We want to stress that a learning culture is a necessary condition for successful use of lessons learned. When a mistake is made, in most organisations the first question to be asked is: 'whose fault is that?' Within a learning culture, there is a shift from blame to accountability, opening possibilities for analysis and constructive dialogue.

5.4. Learning from the organisation: the knowledge centre

In some organisations a special department is responsible for handling internal questions. When knowledge workers find that they lack certain knowledge, they will contact the knowledge centre. If possible, the centre provides an immediate answer. If not, the knowledge centre takes action to collect the necessary knowledge. Knowledge centres are dubbed with various terms: competence centres, knowledge counters, internal helpdesks are examples. Also traditional knowledge technology can be part of this component in the knowledge infrastructure: rule-based systems provide knowledge that can be re-used at different locations and moments in time. In the Netherlands, especially the financial services industry is a primary customer for knowledge technology services, asking for applications that vary from customer acceptance to financial product configuration.

5.5. Learning from the customer: the helpdesk

A helpdesk is comparable to the knowledge centre, but has an external focus: knowledge exchange with customers. On the one hand, it functions as a service to customers, on the other hand it is an inlet for questions, complaints and remarks of customers: these may contain important information for improvement of processes, products and services.

5.6. Learning from industry: benchmarking

Organisations, especially SME's, are often organised in larger bodies. These bodies, apart from other activities, function as a knowledge centre for a particular industry. Knowledge that may be difficult to obtain separately, can be developed and distributed industry-wide. One may think of relevant national or international developments, as well as benchmarking studies, in which the performance of organisations are compared.

Benchmarking Knowledge Management

After a successful study in the USA in 1996, the EFQM (European Foundation for Quality Management), the APQC (American Productivity & Quality Centre) and the Knowledge Management Network (http://kmn.cibit.nl) started a benchmarking study to elicit knowledge management best practices of European organisations. Participating organisations hope to learn from these best practices.

5.7. Learning from the competition: business intelligence

Apart from knowledge about customers, is it also important to develop knowledge about the competition. In which direction is the competition moving? What products and services are being offered? What people do they hire? Who is out there to be hired? This is the domain of business intelligence. It is essential that knowledge developed by the business intelligence component in the knowledge infrastructure be propagated to other components, in order to gain maximum responsiveness to external events.

5.8. Learning from experts: corporate universities

More and more organisations find it necessary to constantly educate and train their employees. Outsourcing of education and training is a decision often made. However, the development of corporate universities is a trend that shows us that especially large organisations choose to do key knowledge transfer and skills development themselves.

Corporate Universities

Organisations that invest in education and training want to have a say in the contents and quality. Corporate universities can be a way to control education and training efforts and results.

Through these institutions, organisations can deliver curricula that they find important in terms of their knowledge policies. Moreover, organisations are capable of offering both theory and practice (because learners find themselves in a 'true' learning environment, something that is often not the case in traditional education). Corporate universities offer the possibility to implement ideas like 'education permanente' without losing touch with the organisational objectives.

Corporate universities come in different forms: from virtual organisations that offer services in an electronic fashion, to fully equipped institutions, specially built for the organisation. Also, strategic alliances with knowledge providers are being made, whereby the providers offer custom-made curricula. In the United States, more than 1,000 corporate universities exist (Meister, 1994).

5.9. Learning from each other: informal meetings

Apart from normal meetings for groups, various organisations support the emergence of communities of practice. In these communities, one aims to have a free flow of knowledge in a multi-disciplinary group, often extending the boundaries of the organisation. This kind of networking is one of the key catalysts in knowledge intensive organisations. However, barriers to a free flow of knowledge are often blocking progress and creativity: non-disclosures, misplaced secrecy, low priorities, lack of travelling budget and lack of a sound technical infrastructure impede collective advancement in a knowledge society.

5.10. Learning by playing: simulation and gaming

Understanding complex domains with intricate interactions between variables is one of the tasks that knowledge workers are confronted with. Understanding consumer behaviour, understanding market dynamics or understanding internal processes in organisations are examples. Understanding how complex systems work is the most important learning discipline, at least according to Peter Senge (1990). Organisations invest in learning facilities that support this understanding: management games, workshops and computer simulations are examples. In a similar fashion, group decisions can be improved by software tools that let users work through decision scenarios.

6. The role of knowledge management

The added value of knowledge infrastructures is not in the individual components per se, but in the synergy between the components. When regarded as an orchestra, the knowledge infrastructure performs best when in harmony. Thus, a collective perspective on the knowledge infrastructure is needed to best gauge its advantages.

From this collective perspective, the role of knowledge management becomes clear: the knowledge management discipline in an organisation is responsible for the design, monitoring and maintenance of a coherent support system for knowledge management: the knowledge infrastructure. It is important to note that the components of a knowledge infrastructure work in concert: connections between the components are just as important as the components themselves. An important accelerator for knowledge infrastructures is the development in information and communication technology (ICT). Using this technology, the possibilities for implementation of components of and coherence in the knowledge infrastructure are numerous. In the following figure, the relation between knowledge management and the knowledge infrastructure is presented.

Figure 3 - The knowledge infrastructure

Each knowledge infrastructure component facilitates a particular learning process. Through the connections between components, it is possible that learning processes augment each other: new knowledge from research is 'pumped into' the helpdesk, which may in turn offer valuable insights for new knowledge development programs. The knowledge management discipline takes on a role of composer and director.

Part 2 of this article will appear in the next issue of Knowledge Management

Eelco Kruizinga, Gertjan van Heijst, Rob van der Spek, are at Kenniscentrum CIBIT, The Netherlands. They can be contacted at:
ekruizinga@cibit.nl
gvheijst@cibit.nl
rvdspek@cibit.nl

Knowledge on the balance sheet

An important reason for the lack of a global perspective on knowledge and knowledge processes is the fact that knowledge is invisible on the balance sheet of an organisation. Despite the fact that it is common opinion that knowledge is one of the most important assets of an organisation, it can not be quantified using traditional models for accounting. The 'intellectual capital' movement tries to put an end to this paradoxical situation by putting knowledge on the balance sheet. Skandia, a financial services firm, can be regarded as a pioneer (Edvinsson et al., 1996). This company developed the Skandia Navigator, an instrument that can be used to report on the financial as well as the intellectual state of an organisation. Leif Edvinsson, Director Intellectual Capital at Skandia (appearing in KM issue 2), points out that the financial report tells how well an organisation performed in the past. The intellectual capital report tells how well an organisation will do in the future.

Just what is intellectual capital? It could be regarded as the difference between stock market value and book value of an organisation. Precisely this difference is normally not shown on the balance sheet of organisations. Intellectual capital itself consists of human capital and structural capital. Structural capital can best be understood by regarding it as 'everything [non-physical] that is left when staff goes home'. It consists of customer capital (e.g. customer base, corporate image, in short goodwill) and organisation capital, which in turn consists of innovation capital (e.g. intellectual properties) and process capital (the ways that organisations have designed and implemented their processes). In order to get intellectual capital on the balance sheet, new ways and languages for accounting are needed: traditional models won't suffice. With a metaphor of the apple tree one can explain that traditional accounting models focus on the apples (i.e. the harvest), whereas intellectual capital accounting focuses on the root system of the apple tree (i.e. that what generates the harvest). In effect, one should turn around the apple tree altogether: letting the financial balance sheet become the annex of the intellectual capital report. Shifting the minds of traditional financial thinking is not easy: it took 6 years at Skandia.

In the intellectual capital movement it is argued that traditionally, accounting didn't only have the wrong focus, but was looking in the wrong direction as well: it was looking at the past. Edvinsson is a strong advocate for what he calls 'futurizing': trying to get grips on the drivers for and in the future. 'Future accounting' requires a new language (and attitude) that goes beyond scenarios.